Read about use cases and practical tips for bringing AI to the enterprise in a chapter excerpt from "Getting Started with Artificial Intelligence." In this episode of the O'Reilly Media Podcast, I sat down with Josh Zheng and Tom Markiewicz, developer advocates for IBM Watson. We discussed how natural language processing (NLP) APIs, and chatbots in particular, represent just one of the ways AI is augmenting humans and boosting productivity in enterprises today. In order to apply AI to the enterprise, Zheng and Markiewicz explain, developers first need to understand the importance of sourcing and cleaning the organization's data, much of which is coming in unstructured formats like email, customer support chats, and PDF documents. This can be "unglamorous" work, but it's also critical to building a successful NLP app, or chatbot.

Then you would want to hear from 7 founders that have built and scaled AI apps to success. Almost consistently, we heard them all say – don't get too consumed by the technology itself, but pay attention to the real human problem you're solving. Be human with your AI app. There's, of course, much more to the advice, so here are 7 founders in their own words, what it takes to develop a successful AI app. Research your user: If you don't know your user you don't know the tool's use.

According to Gartner report, by 2020 about 85% of interaction with consumers will take place without any human participation. It could happen due to Artificial Intelligence and Voice Recognition technologies that are rapidly developing. The apps that work on the basis of Artificial Intelligence should make users' life easier but what principles should be main in such apps? Arkenea developers have consulted the specialists that created programs successfully using Artificial Intelligence. The successful app using Artificial Intelligence gives a "wow-effect", the feeling of magic, the breakthrough that wasn't possible earlier.

The artificial intelligence and voice recognition space has been growing rapidly. According to a Gartner report, by 2020, 85% of customer interactions will be managed without a human. This is pretty much likely, as we are already teaching our machines to interpret data into logical solutions. Apps running on artificial intelligence should make a user's life easy, but what goes into building such apps? To understand it further, we spoke to some successful founders who have built and scaled apps running on artificial intelligence algorithms.

The artificial intelligence and voice recognition space has been growing rapidly. According to a Gartner report, by 2020, 85% of customer interactions will be managed without a human. This is pretty much likely, as we are already teaching our machines to interpret data into logical solutions. Apps running on artificial intelligence should make a user's life easy, but what goes into building such apps? In a #Bitesize interview with us, Xavier Amatriain, VP of engineering at Quora, explained the key to successful machine learning in developing products.